Proteome-wide Mendelian randomization in global biobank meta-analysis reveals multi-ancestry drug targets for common diseases

被引:29
|
作者
Zhao, Huiling [1 ]
Rasheed, Humaria [1 ,2 ,3 ]
Nost, Therese Haugdahl [2 ,4 ]
Cho, Yoonsu [1 ]
Liu, Yi [1 ]
Bhatta, Laxmi [2 ]
Global Biobank Metaanal Initiative, Gibran
Hemani, Gibran [1 ]
Smith, George Davey [1 ,2 ]
Brumpton, Ben Michael [3 ,7 ,8 ]
Zhou, Wei [9 ,10 ,11 ]
Neale, Benjamin M. [10 ,11 ]
Gaunt, Tom R. [1 ,6 ]
Zheng, Jie [1 ,12 ,13 ]
机构
[1] Univ Bristol, Bristol Med Sch, MRC Integrat Epidemiol Unit IEU, Oakfield House, Bristol BS8 2BN, England
[2] Norwegian Univ Sci & Technol, KG Jebsen Ctr Genet Epidemiol, Dept Publ Hlth & Nursing, NTNU, Trondheim, Norway
[3] Univ Oslo, Div Med & Lab Sci, Oslo, Norway
[4] UIT Arctic Univ Norway, Dept Community Med, N-9037 Tromso, Norway
[5] Univ Calif Los Angeles, Inst Quantitat & Computat Biosci, David Geffen Sch Med, Los Angeles, CA USA
[6] NIHR Bristol Biomed Res Ctr, Bristol, England
[7] Norwegian Univ Sci & Technol, NTNU, HUNT Res Ctr, Dept Publ Hlth & Nursing, N-7600 Levanger, Norway
[8] Trondheim Reg & Univ Hosp, St Olavs Hosp, Clin Med, Trondheim, Norway
[9] Univ Michigan, Dept Internal Med, Div Cardiovasc Med, Ann Arbor, MI 48109 USA
[10] Massachusetts Gen Hosp, Analyt & Translat Genet Unit, Boston, MA 02114 USA
[11] Broad Inst Harvard & MIT, Stanley Ctr Psychiat Res, Cambridge, MA 02142 USA
[12] Shanghai Jiao Tong Univ, Ruijin Hosp, Dept Endocrine & Metab Dis, Shanghai Inst Endocrine & Metab Dis,Sch Med, Shanghai, Peoples R China
[13] Shanghai Jiao Tong Univ, Shanghai Natl Clin Res Ctr Metab Dis, Key Lab Endocrine & Metab Dis Natl Hlth Commiss PR, Shanghai Key Lab Endocrine Tumor,State Key Lab Med, Shanghai, Peoples R China
来源
CELL GENOMICS | 2022年 / 2卷 / 11期
基金
英国医学研究理事会; 英国惠康基金;
关键词
HAN CHINESE POPULATION; GENOME; EPIDEMIOLOGY;
D O I
10.1016/j.xgen.2022.100195
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Proteome-wide Mendelian randomization (MR) shows value in prioritizing drug targets in Europeans but with limited evidence in other ancestries. Here, we present a multi-ancestry proteome-wide MR analysis based on cross-population data from the Global Biobank Meta-analysis Initiative (GBMI). We estimated the putative causal effects of 1,545 proteins on eight diseases in African (32,658) and European (1,219,993) ancestries and identified 45 and 7 protein-disease pairs with MR and genetic colocalization evidence in the two ances-tries, respectively. A multi-ancestry MR comparison identified two protein-disease pairs with MR evidence in both ancestries and seven pairs with specific effects in the two ancestries separately. Integrating these MR signals with clinical trial evidence, we prioritized 16 pairs for investigation in future drug trials. Our results highlight the value of proteome-wide MR in informing the generalizability of drug targets for disease preven-tion across ancestries and illustrate the value of meta-analysis of biobanks in drug development.
引用
收藏
页数:25
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